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mradermacher/borealis-27b-i1-GGUF overview

About < quantize version: 2 < output tensor quantised: 1 < convert type: hf < vocab type: < tags: nicoboss < quants: Q2 K IQ3 M Q4 K S IQ3 XXS Q3 K M small IQ4…

transformersggufconversationalinstructborealisgemma3norwegiannorwegian-bokmalnorwegian-nynorskfull-releasenonbnndataset:NbAiLab/aurora-sftbase_model:NbAiLab/borealis-27bbase_model:quantized:NbAiLab/borealis-27blicense:otherendpoints_compatibleregion:usimatrix

Runs locally from ~25.0 MB disk (4 GB VRAM class GPUs with llama.cpp / guIDE).

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Repository Files & Downloads

24 GGUF files detected
Direct downloads for local inference
FileTypeQuantizationSizeLink
borealis-27b.i1-IQ1_M.ggufGGUFIQ1_M6.33 GBDownload
borealis-27b.i1-IQ1_S.ggufGGUFIQ1_S5.83 GBDownload
borealis-27b.i1-IQ2_M.ggufGGUFIQ2_M8.84 GBDownload
borealis-27b.i1-IQ2_S.ggufGGUFIQ2_S8.18 GBDownload
borealis-27b.i1-IQ2_XS.ggufGGUFIQ2_XS7.86 GBDownload
borealis-27b.i1-IQ2_XXS.ggufGGUFIQ2_XXS7.16 GBDownload
borealis-27b.i1-IQ3_M.ggufGGUFIQ3_M11.69 GBDownload
borealis-27b.i1-IQ3_S.ggufGGUFIQ3_S11.33 GBDownload
borealis-27b.i1-IQ3_XS.ggufGGUFIQ3_XS10.77 GBDownload
borealis-27b.i1-IQ3_XXS.ggufGGUFIQ3_XXS9.98 GBDownload
borealis-27b.i1-IQ4_XS.ggufGGUFIQ4_XS13.75 GBDownload
borealis-27b.i1-Q2_K.ggufGGUFQ2_K9.78 GBDownload
borealis-27b.i1-Q2_K_S.ggufGGUFQ2_K_S9.09 GBDownload
borealis-27b.i1-Q3_K_L.ggufGGUFQ3_K_L13.54 GBDownload
borealis-27b.i1-Q3_K_M.ggufGGUFQ3_K_M12.51 GBDownload
borealis-27b.i1-Q3_K_S.ggufGGUFQ3_K_S11.33 GBDownload
borealis-27b.i1-Q4_0.ggufGGUFQ4_014.55 GBDownload
borealis-27b.i1-Q4_1.ggufGGUFQ4_115.99 GBDownload
borealis-27b.i1-Q4_K_M.ggufGGUFQ4_K_M15.41 GBDownload
borealis-27b.i1-Q4_K_S.ggufGGUFQ4_K_S14.60 GBDownload
borealis-27b.i1-Q5_K_M.ggufGGUFQ5_K_M17.95 GBDownload
borealis-27b.i1-Q5_K_S.ggufGGUFQ5_K_S17.48 GBDownload
borealis-27b.i1-Q6_K.ggufGGUFQ6_K20.64 GBDownload
borealis-27b.imatrix.ggufGGUFGGUF25.0 MBDownload

Model Details

Model IDmradermacher/borealis-27b-i1-GGUF
Authormradermacher
Pipeline—
Licenseother
Base modelNbAiLab/borealis-27b
Last modified2026-10-16T01:05:30.000Z

Model README

---

base_model: NbAiLab/borealis-27b

datasets:

  • NbAiLab/aurora-sft

language:

  • no
  • nb
  • nn

library_name: transformers

license: other

mradermacher:

readme_rev: 1

quantized_by: mradermacher

tags:

  • conversational
  • instruct
  • borealis
  • gemma3
  • norwegian
  • norwegian-bokmal
  • norwegian-nynorsk
  • full-release

---

About

<!-- ### quantize_version: 2 -->

<!-- ### output_tensor_quantised: 1 -->

<!-- ### convert_type: hf -->

<!-- ### vocab_type: -->

<!-- ### tags: nicoboss -->

<!-- ### quants: Q2_K IQ3_M Q4_K_S IQ3_XXS Q3_K_M small-IQ4_NL Q4_K_M IQ2_M Q6_K IQ4_XS Q2_K_S IQ1_M Q3_K_S IQ2_XXS Q3_K_L IQ2_XS Q5_K_S IQ2_S IQ1_S Q5_K_M Q4_0 IQ3_XS Q4_1 IQ3_S -->

<!-- ### quants_skip: -->

<!-- ### skip_mmproj: -->

weighted/imatrix quants of https://huggingface.co/NbAiLab/borealis-27b

<!-- provided-files -->

For a convenient overview and download list, visit our model page for this model.

static quants are available at https://huggingface.co/mradermacher/borealis-27b-GGUF

This is a vision model - mmproj files (if any) will be in the static repository.

Usage

If you are unsure how to use GGUF files, refer to one of [TheBloke's

READMEs](https://huggingface.co/TheBloke/KafkaLM-70B-German-V0.1-GGUF) for

more details, including on how to concatenate multi-part files.

Provided Quants

(sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants)

| Link | Type | Size/GB | Notes |

|:-----|:-----|--------:|:------|

| GGUF | imatrix | 0.1 | imatrix file (for creating your own quants) |

| GGUF | i1-IQ1_S | 6.4 | for the desperate |

| GGUF | i1-IQ1_M | 6.9 | mostly desperate |

| GGUF | i1-IQ2_XXS | 7.8 | |

| GGUF | i1-IQ2_XS | 8.5 | |

| GGUF | i1-IQ2_S | 8.9 | |

| GGUF | i1-IQ2_M | 9.6 | |

| GGUF | i1-Q2_K_S | 9.9 | very low quality |

| GGUF | i1-Q2_K | 10.6 | IQ3_XXS probably better |

| GGUF | i1-IQ3_XXS | 10.8 | lower quality |

| GGUF | i1-IQ3_XS | 11.7 | |

| GGUF | i1-IQ3_S | 12.3 | beats Q3_K* |

| GGUF | i1-Q3_K_S | 12.3 | IQ3_XS probably better |

| GGUF | i1-IQ3_M | 12.6 | |

| GGUF | i1-Q3_K_M | 13.5 | IQ3_S probably better |

| GGUF | i1-Q3_K_L | 14.6 | IQ3_M probably better |

| GGUF | i1-IQ4_XS | 14.9 | |

| GGUF | i1-Q4_0 | 15.7 | fast, low quality |

| GGUF | i1-Q4_K_S | 15.8 | optimal size/speed/quality |

| GGUF | i1-Q4_K_M | 16.6 | fast, recommended |

| GGUF | i1-Q4_1 | 17.3 | |

| GGUF | i1-Q5_K_S | 18.9 | |

| GGUF | i1-Q5_K_M | 19.4 | |

| GGUF | i1-Q6_K | 22.3 | practically like static Q6_K |

Here is a handy graph by ikawrakow comparing some lower-quality quant

types (lower is better):

!image.png

And here are Artefact2's thoughts on the matter:

https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9

FAQ / Model Request

See https://huggingface.co/mradermacher/model_requests for some answers to

questions you might have and/or if you want some other model quantized.

Thanks

I thank my company, nethype GmbH, for letting

me use its servers and providing upgrades to my workstation to enable

this work in my free time. Additional thanks to @nicoboss for giving me access to his private supercomputer, enabling me to provide many more imatrix quants, at much higher quality, than I would otherwise be able to.

<!-- end -->

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